Chapter 5. Helper APIs

This chapter covers a number of APIs that you’ll almost certainly use regularly but aren’t used as much as those discussed in Chapter 4.

Programmers, like end users, normally want to refer to things by their domain names instead of their IP addresses. The DNS module provides this lookup facility to you, but it is also used under the hood whenever you are able to use a domain name—for example, in HTTP clients.

The dns module consists of two main methods and a number of convenience methods. The two main methods are resolve(), which turns a domain name into a DNS record, and reverse(), which turns an IP address into a domain. All of the other methods in the dns module are more specialized forms of these methods.

dns.resolve() takes three arguments:

As shown in Example 5-1, calling dns.resolve() is easy, although the callback may be slightly different from other callbacks you’ve used so far.

We called dns.resolve() with the domain and a record type of A, along with a trivial callback that prints results. The first argument of the callback is an error object. If an error occurs, the object will be non-null, and we can consult it to see what went wrong. The second argument is a list of the records returned by the query.

There are convenience methods for all the types of records listed earlier. For example, rather than calling resolve('example.com', 'MX', callback), you can call resolveMx('example.com', callback) instead (see Example 5-2). The API also provides resolve4() and resolve6() methods, which resolve IPv4 and IPv6 address records, respectively.

Because resolve() usually returns a list containing many IP addresses, there is also a convenience method called dns.lookup() that returns just one IP address from an A record query (see Example 5-3). The method takes a domain, an IP family (4 or 6), and a callback. However, unlike .dns.resolve(), it always returns a single address. If you don’t pass an address, it defaults to the network interface’s current setting.

Cryptography is used in lots of places for a variety of tasks. Node uses the OpenSSL library as the basis of its cryptography. This is because OpenSSL is already a well-tested, hardened implementation of cryptographic algorithms. But you have to compile Node with OpenSSL support in order to use the methods in this section.

The cryptograph module enables a number of different tasks. First, it powers the SSL/TLS parts of Node. Second, it contains hashing algorithms such as MD5 or SHA-1 that you might want to use in your application. Third, it allows you to use HMAC.[12] There are some encryption methods to cipher the data with to ensure it is encrypted. Finally, HMAC contains other public key cryptographic functions to sign data and verify signatures.

Each of the functions that cryptography does is contained within a class (or classes), which we’ll look at in the following sections.

Hashes are used for a few important functions, such as obfuscating data in a way that allows it to be validated or providing a small checksum for a much larger piece of data. To use hashes in Node, you should create a Hash object using the factory method crypto.createHash(). This returns a new Hash instance using a specified hashing algorithm. Most popular algorithms are available. The exact ones depend on your version of OpenSSL, but common ones are:

These algorithms all have different advantages and disadvantages. MD5, for example, is used in many applications but has a number of known flaws, including collision issues.[13] Depending on your application, you can pick either a widely deployed algorithm such as MD5 or (preferably) the newer SHA1, or a less universal but more hardened algorithm such as RIPEMD, SHA256, or SHA512.

Once you have data in the hash, you can use it to create a digest by calling hash.update() with the hash data (Example 5-4). You can keep updating a Hash with more data until you want to output it; the data you add to the hash is simply concatenated to the data passed in previous calls. To output the hash, call the hash.digest() method. This will output the digest of the data that was input into the hash with hash.update(). No more data can be added after you call hash.digest().

Notice that the output of the digest is a bit weird. That’s because it’s the binary representation. More commonly, a digest is printed in hex. We can do that by adding 'hex' as a parameter to hash.digest, as in Example 5-5.

When we call hash.digest() again, we get an error. This is because once hash.digest() is called, the Hash object is finalized and cannot be reused. We need to create a new instance of Hash and use that instead. This time we get the hex output that is often more useful. The options for hash.digest() output are binary (default), hex, and base64.

Because data in hash.update() calls is concatenated, the code samples in Example 5-6 are identical.

It is also important to know that although hash.update() looks a lot like a stream, it isn’t really. You can easily hook a stream to hash.update(), but you can’t use stream.pipe().

HMAC combines the hashing algorithms with a cryptographic key in order to stop a number of attacks on the integrity of the signature. This means that HMAC uses both a hashing algorithm (such as the ones discussed in the previous section) and an encryption key. The HMAC API in Node is virtually identical to the Hash API. The only difference is that the creation of an hmac object requires a key as well as a hash algorithm.

crypto.createHmac() returns an instance of Hmac, which offers update() and digest() methods that work identically to the Hash methods we saw in the previous section.

The key required to create an Hmac object is a PEM-encoded key, passed as a string. As shown in Example 5-7, it is easy to create a key on the command line using OpenSSL.

This example creates an RSA in PEM format and puts it into a file, in this case called key.pem. We also could have called the same functionality directly from Node using the process module (discussed later in this chapter) if we omitted the -out key.pem option; with this approach, we would get the results on an stdout stream. Instead we are going to import the key from the file and use it to create an Hmac object and a digest (Example 5-8).

This example uses fs.readFileSync() because a lot of the time, loading keys will be a server setup task. As such, it’s fine to load the keys synchronously (which might slow down server startup time) because you aren’t serving clients yet, so blocking the event loop is OK. In general, other than the use of the encryption key, using an Hmac example is exactly like using a Hash.

The public key cryptography functions are split into four classes: Cipher, Decipher, Sign, and Verify. Like all the other classes in crypto, they have factory methods. Cipher encrypts data, Decipher decrypts data, Sign creates a cryptographic signature for data, and Verify validates cryptographic signatures.

For the HMAC operations, we used a private key. For the operations in this section, we are going to use both the public and private keys. Public key cryptography has matched sets of keys. One, the private key, is kept by the owner and is used to decrypt and sign data. The other, the public key, is made available to other parties. The public key can be used to encrypt data that only the private key owner can read, or to verify the signature of data signed with the private key.

Let’s extract the public key of the private key we generated to do the HMAC digests (Example 5-9). Node expects public keys in certificate format, which requires you to input additional “information.” But you can leave all the information blank if you like.

We simply ask OpenSSL to read in the private key, and then output the public key into a new file called cert.pem in X509 certificate format. All of the operations in crypto expect keys in PEM format.

The Cipher class provides a wrapper for encrypting data using a private key. The factory method to create a cipher takes an algorithm and the private key. The algorithms supported come from those compiled into your OpenSSL implementation:

Many modern cryptographic algorithms use block ciphers. This means that the output is always in standard-size “blocks.” The block sizes vary between algorithms: blowfish, for example, uses 40-byte blocks. This is significant when you are using the Cipher API because the API will always output fixed-size blocks. This helps prevent information from being leaked to an attacker about the data being encrypted or the specific key being used to do the encryption.

Like Hash and Hmac, the Cipher API also uses the update() method to input data. However, update() works differently when used in a cipher. First, cipher.update() returns a block of encrypted data if it can. This is where block size becomes important. If the amount of data in the cipher plus the amount of data passed to cipher.update() is enough to create one or more blocks, the encrypted data will be returned. If there isn’t enough to form a block, the input will be stored in the cipher. Cipher also has a new method, cipher.final(), which replaces the digest() method. When cipher.final() is called, any remaining data in the cipher will be returned encrypted, but with enough padding to make sure the block size is reached (see Example 5-10).

To make the example easier to read, we specified the input and output formats. The input and output formats are both optional and will be assumed to be binary unless specified. For this example, we specified a binary input format because we’re passing a new Buffer (containing whatever random junk was in memory), along with hex output to produce something easier to read. You can see that the first time we call cipher.update(), with 4 bytes of data, we get back an empty string. The second time, because we have enough data to generate a block, we get the encrypted data back as hex. When we call cipher.final(), there isn’t enough data to create a full block, so the output is padded and a full (and final) block is returned. If we sent more data than would fit in a single block, cipher.final() would output as many blocks as it could before padding. Because cipher.final() is just for outputting existing data, it doesn’t accept an input format.

The Decipher class is almost the exact inverse of the Cipher class. You can pass encrypted data to a Decipher object using decipher.update(), and it will stream the data into blocks until it can output the unencrypted data. You might think that since cipher.update() and cipher.final() always give fixed-length blocks, you would have to give perfect blocks to Decipher, but luckily it will buffer the data. Thus, you can pass it data you got off some other I/O transport, such as the disk or network, even though this might give you block sizes different from those used by the encryption algorithm.

Let’s take a look at Example 5-11, which demonstrates encrypting data and then decrypting it.

It is important to make sure both the input and output formats match up for both the plain text and the encrypted data. It’s also worth noting that in order to get a Buffer, you’ll have to make one from the strings returned by Cipher and Decipher.

Although Node abstracts a lot of things from the operating system, you are still running in an operating system and may want to interact more directly with it. Node allows you to interact with system processes that already exist, as well as create new child processes to do work of various kinds. Although Node itself is generally a “fat” thread with a single event loop, you are free to start other processes (threads) to do work outside of the event loop.

The process module enables you to get information about and change the settings of the current Node process. Unlike most modules, the process module is global and is always available as the variable process.

process is an instance of EventEmitter, so it provides events based on systems calls to the Node process. The exit event provides a final hook before the Node process exits (see Example 5-14). Importantly, the event loop will not run after the exit event, so only code without callbacks will be executed.

Because the loop isn’t going to run again, the setTimeout() code will never be evaluated.

An extremely useful event provided by process is uncaughtException (Example 5-15). After you’ve spent any time with Node, you’ll find that exceptions that hit the main event loop will kill your Node process. In many use cases, especially servers that are expected to never be down, this is unacceptable. The uncaughtException event provides an extremely brute-force way of catching these exceptions. It’s really a last line of defense, but it’s extremely useful for that purpose.

Let’s break down what’s happening. First, we create an event listener for uncaughtException. This is not a smart handler; it simply outputs the exception to stdout. If this Node script were running as a server, stdout could easily be used to save the log into a file and capture these errors. However, because it captures the event for a nonexistent function, Node will not exit, but the standard flow is still disrupted. We know that all the JavaScript runs once, and then any callbacks will be run each time their event listener emits an event. In this scenario, because nonexistentFunc() will throw an exception, no code following it will be called. However, any code that has already been run will continue to run. This means that setTimeout() will still call. This is significant when you’re writing servers. Let’s consider some more code in this area, shown in Example 5-16.

This code creates a simple HTTP server and then listens for any uncaught exceptions at the process level. In our HTTP server, the callback deliberately calls a bad function after we’ve sent the HTTP response. Example 5-17 shows the console output for this script.

When we start the example script, the server is available, and we have made a number of HTTP requests to it. Notice that the server doesn’t shut down at any point. Instead, the errors are logged using the function attached to the uncaughtException event. However, we are still serving complete HTTP requests. Why? Node deliberately prevented the callback in process from proceeding and calling console.log(). The error affected only the process we spawned and the server kept running, so any other code was unaffected by the exception encapsulated in one specific code path.

It’s important to understand the way that listeners are implemented in Node. Let’s take a look at Example 5-18.

After an event is emitted, one of the checks in the runtime handler is to see whether there is an array of listeners. If there is more than one listener, the runtime calls the listeners by looping through the array in order. This means that the first attached listener will be called first with apply(), then the second, and so on. What’s important to note here is that all listeners on the same event are part of the same code path. So an uncaught exception in one callback will stop execution for all other callbacks on the same event. However, an uncaught exception in one instance of an event won’t affect other events.

We also get access to a number of system events through process. When the process gets a signal, it is exposed to Node via events emitted by process. An operating system can generate a lot of POSIX system events, which can be found in the sigaction(2) manpage. Really common ones include SIGINT, the interrupt signal. Typically, a SIGINT is what happens when you press Ctrl-C in the terminal on a running process. Unless you handle the signal events via process, Node will just perform the default action; in the case of a SIGINT, the default is to immediately kill the process. You can change default behavior (except for a couple of signals that can never get caught) through the process.on() method (Example 5-19).

To make sure Node doesn’t exit on its own, we read from stdin (described in Operating system input/output) so the Node process continues to run. If you Ctrl-C the program while it’s running, the operating system (OS) will send a SIGINT to Node, which will be caught by the SIGINT event handler. Here, instead of exiting, we log to the console instead.

Process contains a lot of meta-information about the Node process. This can be very helpful when you need to manage your Node environment from within the process. There are a number of properties that contain immutable (read-only) information about Node, such as:

There are also a number of things that you can get and set about the Node process. When the process runs, it does so with a particular user and group. You can get these and set them with process.getgid(), process.setgid(), process.getuid(), and process.setuid(). These can be very useful for making sure that Node is running in a secure way. It’s worth noting that the set methods take either the numerical ID of the group or username or the group/username itself. However, if you pass the group or username, the methods do a blocking lookup to turn the group/username into an ID, which takes a little time.

The process ID, or PID, of the running Node instance is also available as the process.pid property. You can set the title that Node displays to the system using the process.title property. Whatever is set in this property will be displayed in the ps command. This can be extremely useful when you are running multiple Node processes in a production environment. Instead of having a lot of processes called node, or possibly node app.js, you can set names intelligently for easy reference. When one process is hogging CPU or RAM, it’s great to have a quick idea of which one is doing so.

Other available information includes process.execPath, which shows the execution path of the current Node binary (e.g., /usr/local/bin/node). The current working directory (to which all files opened will be relative) is accessible with process.cwd(). The working directory is the directory you were in when Node was started. You can change it using process.chdir() (this will throw an exception if the directory is unreadable or doesn’t exist). You can also get the memory usage of the current Node process using process.memoryUsage(). This returns an object specifying the size of the memory usage in a couple of ways: rss shows how much RAM is being used, and vsize shows the total memory used, including both RAM and swap. You’ll also get some V8 stats: heapTotal and heapUsed show how much memory V8 has allocated and how much it is actively using.

There are a number of places where you can interact with the OS (besides making changes to the Node process in which the program is running) from process. One of the main ones is having access to the standard OS I/O streams. stdin is the default input stream to the process, stdout is the process’s output stream, and stderr is its error stream. These are exposed with process.stdin, process.stdout, and process.stderr, respectively. process.stdin is a readable stream, whereas process.stdout and process.stderr are writable streams.

stderr is used to output exceptions and problems with program execution. In POSIX systems, because it is a separate stream, output logs and error logs can be easily redirected to different destinations. This can be very desirable, but in Node it comes with a couple of caveats. When you write to stderr, Node guarantees that the write will happen. However, unlike a regular stream, this is done as a blocking call. Typically, calls to Steam.write() return a Boolean value indicating whether Node was able to write to the kernel buffer. With process.stderr this will always be true, but it might take a while to return, unlike the regular write(). Typically, it will be very fast, but the kernel buffer may sometimes be full and hold up your program. This means that it is generally inadvisable to write a lot to stderr in a production system, because it may block real work.

One final thing to note is that process.stderr is always a UTF-8 stream. Any data you write to process.stderr will be interpreted as UTF-8 without you having to set an encoding. Moreover, you are not able to change the encoding here.

Another place where Node programmers often touch the operating system is to retrieve the arguments passed when their program is started. argv is an array containing the command-line arguments, starting with the node command itself (see Examples 5-22 and 5-23).

There are few things to notice here. First, the process.argv array is simply a split of the command line based on whitespace. If there are many characters of whitespace between two arguments, they count as only a single split. The check for whitespace is written as \s+ in a regular expression (regex). This doesn’t count for whitespace in quotes, however. Quotes can be used to keep tokens together. Also, notice how the first file argument is expanded. This means you can pass a relative file argument on the command line, and it will appear as its absolute pathname in argv. This is also true for special characters, such as using ~ to refer to the home directory. Only the first argument is expanded this way.

argv is extremely helpful for writing command-line scripts, but it’s pretty raw. There are a number of community projects that extend its support to help you easily write command-line applications, including support for automatically enabling features, writing inline help systems, and other more advanced features.

If you’ve done work with JavaScript in browsers, you’ll be familiar with setTimeout(). In Node, we have a much more direct way to access the event loop and defer work that is extremely useful. process.nextTick() creates a callback to be executed on the next “tick,” or iteration of the event loop. While it is implemented as a queue, it will supersede other events. Let’s explore that a little bit in Example 5-24.

This example creates an HTTP server. The request event listener on the server creates a callback using process.nextTick(). No matter how many requests we make to the HTTP server, the “tick” will always occur on the next pass of the event loop. Unlike other callbacks, nextTick() callbacks are not a single event and thus are not subject to the usual callback exception brittleness, as shown in Examples 5-25 and 5-26.

Despite the deliberate error, unlike other event callbacks on a single event, each of the ticks is isolated. Let’s walk through the code. First, we set an exception handler to catch any exceptions. Next, we set a number of callbacks on process.nextTick(). Each of these callbacks outputs to the console; however, the second has a deliberate error. Finally, we log a message to the console. When Node runs the program, it evaluates all the code, which includes outputting 'End of 1st loop'. Then it calls the callbacks on nextTick() in order. First 'tick' is outputted, and then we throw an error. This is because we hit our deliberate mistake on the next tick. The error causes process to emit() an uncaughtException event, which runs our function to output the error to the console. Because we threw an error, 'tock' was not outputted to the console. However, 'tick tock' still is. This is because every time nextTick() is called, each callback is created in isolation. You could consider the execution of events to be emit(), which is called inline in the current pass of event loop; nextTick(), which is called at the beginning of the event loop in preference to other events; and finally, other events in order at the beginning of the event loop.

The child_process module allows you to create child processes of your main Node process. Because Node has only one event loop in a single process, sometimes it is helpful to create child processes. For example, you might do this to make use of more cores of your CPU, because a single Node process can use only one of the cores. Or, you could use child_process to launch other programs and let Node interact with them. This is extremely helpful when you’re writing command-line scripts.

There are two main methods in child_process. spawn() creates a child process with its own stdin, stdout, and stderr file descriptors. exec() creates a child process and returns the result as a callback when the process is complete. This is an extremely versatile way to create child processes, a way that is still nonblocking but doesn’t require you to write extra code in order to steam forward.

All child processes have some common properties. They each contain properties for stdin, stdout, and stderr, which we discussed in Operating system input/output. There is also a pid property that contains the OS process ID of the child. Children emit the exit event when they exit. Other data events are available via the stream methods of child_process.stdin, child_process.stdout, and child_process.stderr.

Let’s start with exec() as the most straightforward use case. Using exec(), you can create a process that will run some program (possibly another Node program) and then return the results for you in a callback (Example 5-27).

When you call exec(), you can pass a shell command for the new process to run. Note that the entire command is a string. If you need to pass arguments to the shell command, they should be constructed into the string. In the example, we passed ls the -l argument to get the long form of the output. You can also include complicated shell features, such as | to pipe commands. Node will return the results of the final command in the pipeline.

The callback function receives three arguments: an error object, the result of stdout, and the result of stderr. Notice that just calling ls will run it in the current working directory of Node, which you can retrieve by running process.cwd().

It’s important to understand the difference between the first and third arguments. The error object returned will be null unless an error status code is returned from the child process or there was another exception. When the child process exits, it passes a status up to the parent process. In Unix, for example, this is 0 for success and an 8-bit number greater than 0 for an error. The error object is also used when the command called doesn’t meet the constraints that Node places on it. When an error code is returned from the child process, the error object will contain the error code and stderr. However, when a process is successful, there may still be data on stderr.

exec() takes an optional second argument with an options object. By default, this object contains the properties shown in Example 5-28.

The properties are:

Let’s set some of the options to put constraints on a process. First, let’s try restricting the Buffer size of the response, as demonstrated in Example 5-29.

In this example, you can see that when we set a tiny maxBuffer (just 1 kilobyte), running ls quickly exhausted the available space and threw an error. It’s important to check for errors so that you can deal with them in a sensible way. You don’t want to cause an actual exception by trying to access resources that are unavailable because you’ve restricted the child_process. If the child_process returns with an error, its stdin and stdout properties will be unavailable and attempts to access them will throw an exception.

It’s also possible to stop a Child after a set amount of time, as shown in Example 5-30.

This example defines a deliberately long-running process (counting from 1 to 100,000 in a shell script), but we also set a short timeout. Notice that we also specified a killSignal. By default, the kill signal is SIGTERM, but we used SIGKILL to show the feature.[14] When we get the error back, notice there is a killed property that tells us that Node killed the process and that it didn’t exit voluntarily. This is also true for the previous example. Because it didn’t exit on its own, there isn’t a code property or some of the other properties of a system error.

spawn() is very similar to exec(). However, it is a more general-purpose method that requires you to deal with streams and their callbacks yourself. This makes it a lot more powerful and flexible, but it also means that more code is required to do the kind of one-shot system calls we accomplished with exec(). This means that spawn() is most often used in server contexts to create subcomponents of a server and is the most common way people make Node work with multiple cores on a single machine.

Although it performs the same function as exec(), the API for spawn() is slightly different (see Examples 5-31 and 5-32). The first argument is still the command to start the process with, but unlike exec(), it is not a command string; it’s just the executable. The process’s arguments are passed in an array as the (optional) second argument to spawn(). It’s like an inverse of process.argv: instead of the command being split() across spaces, you provide an array to be join()ed with spaces.

Finally, spawn() also takes an options array as the final argument. Some of these options are the same as exec(), but we’ll cover that in more detail shortly.

In this example, we’re using the Unix program cat, which simply echoes back whatever input it gets. You can see that, unlike exec(), we don’t issue a callback to spawn() directly. That’s because we are expecting to use the Streams provided by the Child class to get and send data. We named the variable with the instance of Child “cat,” and so we can access cat.stdout to set events on the stdout stream of the child process. We set a listener on cat.stdout to watch for any data events, and we set a listener on the child itself in order to watch for the exit event. We can send our new child data using stdin by accessing its child.stdin stream. This is just a regular writable stream. However, as a behavior of the cat program, when we close stdin, the process exits. This might not be true for all processes, but it is true for cat, which exists only to echo back data.

The options that can be passed to spawn() aren’t exactly the same as exec(). This is because you are expected to manage more things by hand with spawn(). The env, setsid, and cwd properties are all options for spawn(), as are uid and gid, which set the user ID and the group ID, respectively. Like process, setting the uid or the gid to a username or a group name will block briefly while the user or group is looked up. There is one more option for spawn() that doesn’t exist for exec(): you can set custom file descriptors that will be given to the new child process. Let’s take some time to cover this topic because it’s a little complex.

A file descriptor in Unix is a way of keeping track of which programs are doing what with which files. Because Unix lets many programs run at the same time, there needs to be a way to make sure that when they interact with the filesystem they don’t accidentally overwrite someone else’s changes. The file descriptor table keeps track of all the files that a process wants to access. The kernel might lock a particular file to stop two programs from writing to the file at the same time, as well as other management functions. A process will look at its file descriptor table to find the file descriptor representing a particular file and pass that to the kernel to access the file. The file descriptor is simply an integer.

The important thing is that the name “file descriptor” is a little deceptive because it doesn’t represent only pure files; network and other sockets are also allocated file descriptors. Unix has interprocess communications (IPC) sockets that let processes talk to each other. We’ve been calling them stdin, stdout, and stderr. This is interesting because spawn() lets us specify file descriptors when starting a new child process. This means that instead of the OS assigning a new file descriptor, we can ask child processes to share an existing file descriptor with the parent process. That file descriptor might be a network socket to the Internet or just the parent’s stdin, but the point is that we have a powerful way of delegating work to child processes.

How does this work in practice? When passing the options object to spawn(), we can specify customFds to pass our own three file descriptors to the child instead of them creating a stdin, stdout, and stderr file descriptor (Examples 5-33 and 5-34).

The file descriptors 0, 1, and 2 represent stdin, stdout, and stderr, respectively. In this example, we create a child and pass it stdin, stdout, and stderr from the parent Node process. We can test this wiring using the command line. The echo command outputs a string “foo.” If we pass that directly to node with a pipe (stdout to stdin), we get an error. We can, however, pass it to the cat command, which echoes it back. Also, if we pipe to the Node process running our script, it echoes back. This is because we’ve hooked up the stdin, stdout, and stderr of the Node process directly to the cat command in our child process. When the main Node process gets data on stdin, it gets passed to the cat child process, which echoes it back on the shared stdout. One thing to note is that once you wire up the Node process this way, the child process loses its child.stdin, child.stdout, and child.stderr file descriptor references. This is because once you pass the file descriptors to the process, they are duplicated and the kernel handles the data passing. Consequently, Node isn’t in between the process and the file descriptors (FDs), so you cannot add events to those streams (see Examples 5-35 and 5-36).

When custom file descriptors are specified, the streams are literally set to null and are completely inaccessible from the parent. It is still preferable in many cases, though, because routing through the kernel is much faster than using something like stream.pipe() with Node to connect the streams together. However, stdin, stdout, and stderr aren’t the only file descriptors worth connecting to child processes. A very common use case is connecting network sockets to a number of children, which allows for multicore utilization.

Say we are creating a website, a game server, or anything that has to deal with a bunch of traffic. We have this great server that has a bunch of processors, each of which has two or four cores. If we simply started a Node process running our code, we’d have just one core being used. Although CPU isn’t always the critical factor for Node, we want to make sure we get as close to the CPU bound as we can. We could start a bunch of Node processes with different ports and load-balance them with Nginx or Apache Traffic Server. However, that’s inelegant and requires us to use more software. We could create a Node process that creates a bunch of child processes and routes all the requests to them. This is a bit closer to our optimal solution, but with this approach we just created a single point of failure because only one Node process routes all the traffic. This isn’t ideal. This is where passing custom FDs comes into its own. In the same way that we can pass the stdin, stdout, and stderr of a master process, we can create other sockets and pass those in to child processes. However, because we are passing file descriptors instead of messages, the kernel will deal with the routing. This means that although the master Node process is still required, it isn’t bearing the load for all the traffic.

assert is a core library that provides the basis for testing code. Node’s assertions works pretty much like the same feature in other languages and environments: they allow you to make claims about objects and function calls and send out messages when the assertions are violated. These methods are really easy to get started with and provide a great way to unit test your code’s features. Node’s own tests are written with assert.

Most assert methods come in pairs: one method providing the positive test and the other providing the negative one. For instance, Example 5-37 shows equal() and notEqual(). The methods take two arguments: the first is the expected value, and the second is the actual value.

The most obvious thing here is that when an assert method doesn’t pass, it throws an exception. This is a fundamental principle in the test suites. When a test suite runs, it should just run, without throwing an exception. If that is the case, the test is successful.

There are just a few assertions. equal() and notEqual() check for the == equality and != inequality operators. This means they test weakly for truthy and falsy values, as Crockford termed them. In brief, when tested as a Boolean, falsy values consist of false, 0, empty strings (i.e., ""), null, undefined, and NaN. All other values are truthy. A string such as "false" is truthy. A string containing "0" is also truthy. As such, equal() and notEqual() are fine to compare simple values (strings, numbers, etc.) with each other, but you should be careful checking against Booleans to ensure you got the result you wanted.

The stringEqual() and notStrictEqual() methods test equality with === and !==, which will ensure that only actual values of true and false are treated as true and false, respectively. The ok() method, shown in Example 5-38, is a shorthand for testing whether something is truthy, by comparing the value with true using ==.

Often the things you want to compare aren’t simple values, but objects. JavaScript doesn’t have a way to let objects define equality operators on themselves, and even if it did, people often wouldn’t define the operators. So the deepEqual() and notDeepEqual() methods provide a way of deeply comparing object values. Without going into too many of the gory details, these methods perform a few checks. If any check fails, the test throws an exception. The first test checks whether the values simply match with the === operator. Next, the values are checked to see whether they are Buffers and, if so, they are checked for their length, and then checked byte by byte. Next, if the object types don’t match with the == operator, they can’t be equal. Finally, if the arguments are objects, more extensive tests are done, comparing the prototypes of the two objects and the number of properties, and then recursively performing deepEqual() on each property.

The important point here is that deepEqual() and notDeepEqual() are extremely helpful and thorough, but also potentially expensive. You should try to use them only when needed. Although these methods will attempt to do the most efficient tests first, it can still take a bit longer to find an inequality. If you can provide a more specific reference, such as the property of an object rather than the whole object, you can significantly improve the performance of your tests.

The next assert methods are throws() and doesNotThrow(). These check whether a particular block of code does or doesn’t throw an exception. You can check for a specific exception or just whether any exception is thrown. The methods are pretty straightforward, but have a few options that are worth reviewing.

It might be easy to overlook these tests, but handling exceptions is an essential part of writing robust JavaScript code, so you should use the tests to make sure the code you write throws exceptions in all the correct places. Chapter 3 offers more information on how to deal with exceptions well.

To pass blocks of code to throws() and doesNotThrow(), wrap them in functions that take no arguments (see Example 5-39). The exception being tested for is optional. If one isn’t passed, throws() will just check whether any exception happened, and doesNotThrow() will ensure that an exception hasn’t been thrown. If a specific error is passed, throws() will check that the specified exception and only that exception was thrown. If any other exceptions are thrown or the exception isn’t thrown, the test will not pass. For doesNotThrow(), when an error is specified, it will continue without error if any exception other than the one specified in the argument is thrown. If an exception matching the specified error is thrown, it will cause the test to fail.

There are four ways to specify the type of error to look for or avoid. Pass one of the following:

The vm, or Virtual Machine, module allows you to run arbitrary chunks of code and get a result back. It has a number of features that allow you to change the context in which the code runs. This can be useful to act as a kind of faux sandbox. However, the code is still running in the same Node process, so you should be cautious. vm is similar to eval(), but offers some more features and a better API for managing code. It doesn’t have the ability to interact with the local scope in the way that eval() does, however.

There are two ways to run code with vm. Running the code “inline” is similar to using eval(). The second way is to precompile the code into a vm.Script object. Let’s have a look at Example 5-40, which demonstrates running code inline using vm.

So far, vm looks a lot like eval(). We pass some code to it, and we get a result back. However, vm doesn’t interact with local scope in the same way that eval() does. Code run with eval() will behave as if it were truly inline and replaces the eval() method call. But calls to vm methods will not interact with the local scope. So eval() can change the surrounding context, whereas vm cannot, as shown in Example 5-41.

We’ve created two variables, e and v. When we use the e variable with eval(), the end result of the statement applies back to the main context. However, when we try the same thing with v and vm.runInThisContext(), we get an exception because we refer to v on the right side of the equals sign, and that variable is not defined. Whereas eval() runs in the local scope, vm does not.

The vm subsystem actually maintains its own local context that persists from one invocation of vm to another. Thus, if we create v within the scope of the vm, the variable subsequently is available to later vm invocations, maintaining the state in which the first vm left it. However, the variable from the vm has no impact on v in the local scope of the main event loop.

It’s also possible to pass a preexisting context to vm. This context will be used in place of the default context.

Example 5-42 uses vm.runInNewContext(), which takes a context object as a second argument. The scope of that object becomes the context for the code we run with vm. If we continue to pass it from object to object, the context will be modified. However, the context is also available to the global scope.

You can also compile vm.Script objects (Example 5-43). These save a piece of code that you can then run repeatedly. At runtime, you can choose the context to be applied. This is helpful when you are repeatedly running the same code against multiple contexts.

This example reads in a JavaScript file that contains the simple command console.log(output);. we compile this into a script object, which means we can then run script.runInNewContext() on the script and pass in a context. We deliberately triggered an error to show that, just as when running vm.runInNewContext(), you need to pass in the objects to which you refer (such as the console object); otherwise, even basic global functions are not available. It’s also worth noting that the exception is thrown from undefined:1:1.

All the vm run commands take a filename as an optional final argument. It doesn’t change the functionality, but allows you to set the name of the file that appears in a message when an error is thrown. This is useful if you load a lot of files from disk and run them because it tells you which piece of code threw an error. The parameter is totally arbitrary, so you could use whatever string is meaningful to help you debug the code.



[12] Hash-based Message Authentication Code (HMAC) is a crytographic way of verifying data. It is often used like hashing algorithms to verify that two pieces of data match, but it also verifies that the data hasn’t been tampered with.

[13] It’s possible to deliberately make two pieces of data with the same MD5 checksum, which for some purposes can make the algorithm less desirable. More modern algorithms are less prone to this, although people are finding similar problems with SHA1 now.

[14] SIGKILL can be invoked in the shell through kill -9.